Chronic diseases are often expressed by episodic worsening of clinical symptoms. Preventive treatment of chronic diseases reduces the overall dosage of required medication and associated side effects, and lowers mortality and morbidity. Generally, preventive treatment should be initiated or intensified as soon as the earliest clinical symptoms are detected, in order to prevent progression and worsening of the clinical episode and to stop and reverse the pathophysiological process. Therefore, the ability to accurately monitor pre-episodic indicators increases the effectiveness of preventive treatment of chronic diseases.
Many chronic diseases cause systemic changes in vital signs, such as breathing and heartbeat patterns, through a variety of physiological mechanisms. For example, common respiratory disorders, such as asthma, chronic obstructive pulmonary disease (COPD), sleep apnea and cystic fibrosis (CF), are direct modifiers of breathing and/or heartbeat patterns. Other chronic diseases, such as diabetes, epilepsy, and certain heart conditions (e.g., congestive heart failure (CHF)), are also known to modify cardiac and breathing activity. In the case of certain heart conditions, such modifications typically occur because of pathophysiologies related to fluid retention and general cardiovascular insufficiency. Other signs such as coughing and sleep restlessness are also known to be of importance in some clinical situations.
Many chronic diseases induce systemic effects on vital signs. For example, some chronic diseases interfere with normal breathing and cardiac processes during wakefulness and sleep, causing abnormal breathing and heartbeat patterns.
Breathing and heartbeat patterns may be modified via various direct and indirect physiological mechanisms, resulting in abnormal patterns related to the cause of modification. Some respiratory diseases, such as asthma, and some heart conditions, such as CHF, are direct breathing modifiers. Other metabolic abnormalities, such as hypoglycemia and other neurological pathologies affecting autonomic nervous system activity, are indirect breathing modifiers.
The following patents and patent application publications, all of which are incorporated herein by reference, may also be of interest:
U.S. Pat. No. 4,657,026 to Tagg;
U.S. Pat. No. 5,235,989 to Zomer;
U.S. Pat. No. 5,540,734 to Zabara;
U.S. Pat. No. 5,743,263 to Baker;
U.S. Pat. No. 5,957,861 to Combs;
U.S. Pat. No. 5,964,720 to Pelz;
U.S. Pat. No. 6,134,970 to Kumakawa;
U.S. Pat. No. 6,375,621 to Sullivan;
U.S. Pat. No. 6,383,142 to Gavriely;
U.S. Pat. No. 6,436,057 to Goldsmith et al.;
U.S. Pat. No. 6,856,141 to Ariav;
U.S. Pat. No. 6,980,679 to Jeung;
U.S. Pat. No. 6,984,207 to Sullivan;
U.S. Pat. No. 6,984,993 to Ariav;
U.S. Pat. No. 7,025,729 to de Chazal;
US Patent Application 2003/0045806, issued as U.S. Pat. No. 6,547,743, to Brydon;
US Patent Application 2005/0119586, issued as U.S. Pat. No. 7,267,652, to Coyle et al.;
US Patent Application 2006/0084848 to Mitchnick;
US Patent Application 2007/0156031, issued as U.S. Pat. No. 7,629,890 to Sullivan;
US Patent Application Publication 2007/0249952 to Rubin et al.; and
US Patent Application Publication 2008/0005838, issued as U.S. Pat. No. 7,699,784, to Wan Fong et al.
The following articles, which are incorporated herein by reference, may also be of interest:
Alihanka J., et al., “A new method for long-term monitoring of the ballistocardiogram, heart rate, and respiration,” Am J Physiol Regul Integr Comp Physiol 240:384-392 (1981).
Bentur, L. et al., “Wheeze monitoring in children for assessment of nocturnal asthma and response to therapy,” Eur Respir J 21(4):621-626 (2003).
Bilmes, J., “A gentle tutorial on the EM algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models,” Technical report, University of Berkeley, ICSI-TR-97-021, 1997.
Chang, A. B. et al., “Cough, airway inflammation, and mild asthma exacerbation,” Archives of Disease in Childhood 86:270-275 (2002).
Dempster, A. P., N. M. Laird, and D. B. Rubin, “Maximum likelihood from incomplete data via the EM algorithm,” Journal of the royal statistical society, vol. 39 B, pp. 1-38, 1977.
Hirtum, A.; Berckmans, D.; Demuynck, K.; and Compernolle, D., “Autoregressive Acoustical Modelling of Free Field Cough Sound,” Proc. International Conference on Acoustics, Speech and Signal Processing, volume I, pages 493-496, Orlando, U.S.A., May 2002.
Hsu, J. Y., et al., “Coughing frequency in patients with persistent cough: assessment using a 24 hour ambulatory recorder,” Eur Respir J 7:1246-1253 (1994).
Hudgel, D. W., R. J. Martin, B. Johnson, and P. Hill, “Mechanics of the respiratory system during sleep in normal humans,” J. Appl. Physiol., vol. 5, pp. 133-137, 1984.
Kandtelhardt, J. W., T. Penzel, S. Rostig, H. F. Becker, S. Halvin, and A. Bunde, Breathing during REM and non-REM sleep: correlated versus uncorrelated behavior,” Physica. A., vol. 319, pp. 447-457, 2003.
Li, Q. and A. Barron, “Mixture density estimation,” Advances in neural information processing systems, vol. 12, pp. 279-285, MIT press, 2000.
Mack, D., et al., “Non-invasive analysis of physiological signals: NAPS: A low cost, passive monitor for sleep quality and related applications,” University of Virginia Health System (undated).
O'Connor C J et al, “Identification of endotracheal tube malpositions using computerized analysis of breath sounds via electronic stethoscopes,” Anesth Analg 2005; 101:735-9.
Oppenheim, A. V., and R. W. Schafer, Discrete-Time Signal Processing, Prentice-Hall, 1989, pp. 311-312. Rechtschaffen A., Kales A. Manual of standardized terminology, techniques and scoring system for sleep for sleep stages of human subjects. Los Angeles: UCLA brain information services/brain research institute, 1968.
Salmi, T., et al., “Automatic analysis of sleep records with static charge sensitive bed,” Electroencephalography and Clinical Neurophysiology 64:84-87 (1986).
Schwarz, G., “Estimating the dimension of a model,” Annals of statistics, vol. 6, pp. 461-464, 1978.
Sorvoja, H. and Myllylä, R., “Noninvasive blood pressure measurement methods,” Molecular and Quantum Acoustics. vol. 27, 2006.
Van der Loos, H. F. M., et al., “Unobtrusive vital signs monitoring from a multisensor bed sheet,” RESNA '2001, Reno, Nev., Jun. 22-26, 2001.
Waris, M., et al., “A new method for automatic wheeze detection,” Technol Health Care 6(1):33-40 (1998).
Watanabe, T., et al., “Noncontact Method for Sleep Stage Estimation,” IEEE Transactions on Biomedical Engineering, No 10, Vol. 51, October 2004.
Whitney, C. W., Gottlieb D J, Redline S, Norman R G, Dodge R R, Shahar E, Surovec S and Nieto F J, “Reliability of scoring respiratory disturbance indices and sleep staging,” Sleep, 1998, November 2; 21(7): 749-757.
Yongjoon, C., et al., “Air mattress sensor system with balancing tube for unconstrained measurement of respiration and heart beat movements”, 2005 Physiol. Meas. 26 413-422.
U.S. Pat. No. 7,077,810 to Lange et al., which is assigned to the assignee of the present application and is incorporated herein by reference, describes a method for predicting an onset of a clinical episode, the method including sensing breathing of a subject, determining at least one breathing pattern of the subject responsively to the sensed breathing, comparing the breathing pattern with a baseline breathing pattern, and predicting the onset of the episode at least in part responsively to the comparison.
U.S. Provisional Patent Applications 60/541,779, 60/674,382 and 60/692,105, PCT Publication WO 05/074361 to Lange et al., US Patent Application Publication 2006/0241510, issued as U.S. Pat. No. 7,314,451, to Halperin et al., US Patent Application 2008/0275349 submitted by Halperin et al. on May 1, 2008 assigned to the assignee of the present invention and US Patent Application Publication 2007/0118054 to Pinhas et al. know abandoned), all of which are assigned to the assignee of the present application and incorporated herein by reference, describe various methods and systems for clinical episode prediction and monitoring.
The inclusion of the foregoing references in this Background section does not imply that they constitute prior art or analogous art with respect to the invention disclosed herein.